Manager, Data Science - New York
2 days ago

Job description
Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click "Apply to Job" online on this web page.Responsibilities
- Help build and lead data science teams on projects to deliver world-class products.
- Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how users interact with our products.
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
- Manage development of data resources, gather requirements, organize sources, and support product launches and data science projects.
- Analyze data, business intelligence, and statistical results to identify actionable insights, suggest recommendations, and influence the direction of Facebook's product decisions and product launches by effectively communicating results to cross-functional groups, including Online Ops, Product, and Engineering teams.
- Will leverage data to provide insights about user behavior and to inform business decisions.
- Make business recommendations based on data mining on large, complex data sets and applying concepts in number theory, computational theory, data structures, and algorithms.
- Predict and understand user patterns through analytical and statistical metric analysis.
- Apply quantitative skills in predictive modeling, business intelligence analysis, A/B tests, regression models, and machine learning to gather data insights.
- Requires a PhD degree (or foreign equivalent) in Applied Physics, Computer Science, Engineering, Sciences, Mathematics, Statistics, Physics, or related field. Requires completion of a university-level course, research project, internship, or thesis in the following:
- Machine learning techniques
- Statistical analysis using R, MATLAB, SPSS, Python, or Perl
- Quantitative analysis techniques: clustering, regression, pattern recognition, or descriptive and inferential statistics
- Communicating and presenting results of data analyses
- Building and analyzing reports and key data sets to empower operations and exploratory analysis
- Translating strategic questions into structured analyses, defining success metrics, and developing reporting
- Building key statistical data sets to empower operational and exploratory analysis and automating analyses
- Assisting in designing hypothesis testing experiments, analyzing data collected, and presenting results
- Conducting ad hoc data analysis based on current team needs
- Mentoring junior team members on defining problems and hypothesis, experimentation, and analytical skills
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